Evaluation of Sustainable Green Materials: Pinecone in Permeable Adsorptive Barriers for Remediation of Groundwater Contaminated by $Pb^{2+}$ and Methylene Blue

TL;DR

This study evaluates pinecone-based materials as sustainable alternatives to activated carbon in permeable barriers for groundwater remediation, demonstrating effective removal of lead ions and methylene blue with high model accuracy.

Contribution

It introduces raw pinecone powder and biochar as eco-friendly, effective materials for in situ groundwater remediation in permeable barriers, with comprehensive kinetic and regression modeling.

Findings

Pinecone materials effectively reduce Pb²⁺ levels in groundwater.

Gaussian Process models outperform exponential models in explaining remediation.

High correlation (R² > 0.99) between models and actual removal data.

Abstract

We report herein, the potential of raw pinecone powder (PCP) and pinecone biochar (PCBC) as alternatives to activated carbon used in Permeable Adsorptive Barriers (PABs) for the in situ remediation of polluted groundwater. A constructed lab-scale unconfined aquifer ($38\times30\times17$ $cm$) fitted with PCP and PCBC PABs ($21\times3\times20$ $cm$), was evaluated for the removal of $Pb^{2+}$ ions in a continuous flow setup. Results indicate that after $3600$ minutes, PCP was able to reduce $Pb^{2+}$ ions from a Co=$50$ $mg/L$ to $7.94$ $mg/L$ for the first run and $19.4$ $mg/L$ for a second run, respectively. Comparatively, PCBC reached $6.5$ $mg/L$ for the first run and $8.94$ for the second run. It was confirmed that adsorption was best described by the first-order kinetic model with $R^2$ values above $0.95$. Maximum adsorption capacity values were found to be $1.00$, $0.63$, $1.08$, and $0.85$ mg/g for each scenario respectively. In addition, nonlinear regression models of exponential and Gaussian Processes are fit to explain remediation by time for $Pb^{2+}$ and Methylene Blue. Gaussian Processes are able to better explain the variation of pollution removal compared to simpler exponential models. When regressed against true removal percentages all models are able to provide $R^2>0.99$.